The impacts of economic reform on the efficiency of silviculture: a non-parametric approach
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Bibliographic record
Abstract
Institutions and organizations are regarded as being important in determining the efficiency of economic agents and public units. This study first reviews the economic reforms in silvicultural activities in China's state-owned forestry bureaux, then empirically examines the impact of economic reforms. Panel data from 40 forestry bureaux in Heilongjiang Province, and two different economic regimes: from the pre-reform and economic transition periods, are analyzed by Data Envelopment Analysis (DEA). The technical efficiency has been decomposed into pure technical efficiency and scale efficiency and then examined. Our results show that the economic reforms have increased efficiency on average by about 25 per cent. Moreover, the study qualitatively analyses the sources of improvement and argues that the efficiency gain is a result of reductions in labour shirking and administration costs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it